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The extended Bregman divergence and parametric estimation
Sancharee Basak, Ayanendranath Basu
Minimization of suitable statistical distances~(between the data and model densities) has proved to be a very useful technique in the field of robust inference. Apart from the clas…
On minimum Bregman divergence inference
Soumik Purkayastha, Ayanendranath Basu
In this paper a new family of minimum divergence estimators based on the Bregman divergence is proposed. The popular density power divergence (DPD) class of estimators is a sub-cla…
On Robust Pseudo-Bayes Estimation for the Independent Non-homogeneous Set-up
Tuhin Majumder, Ayanendranath Basu, Abhik Ghosh
The ordinary Bayes estimator based on the posterior density suffers from the potential problems of non-robustness under data contamination or outliers. In this paper, we consider t…
Density Power Downweighting and Robust Inference: Some New Strategies
Saptarshi Roy, Kaustav Chakraborty, Somnath Bhadra +1
Preserving the robustness of the procedure has, at the present time, become almost a default requirement for statistical data analysis. Since efficiency at the model and robustness…
Power and Level Robustness of A Composite Hypothesis Testing under Independent Non-Homogeneous Data
Abhik Ghosh, Ayanendranath Basu
Robust tests of general composite hypothesis under non-identically distributed observations is always a challenge. Ghosh and Basu (2018, Statistica Sinica, 28, 1133--1155) have pro…